Our current work focuses on the security and privacy-preservation of big data, protocols resilient to sensitive information leakage, and cryptographic primitives, such as encryption, signature, authentication etc, resist on new kinds of attacks in open networks. Also, we give the cryptographic implementions for secure protocols and applications. Big Data Security. Big data is now an immensely developing trend, where the big data is to process large amounts of data, regardless of its data structure. From a security perspective, there are three distinct issues to be considered since authentication and access to data from many locations may not be sufficiently controlled.: The first one is how to keep the sensitive data security in a huge quantity of data pools; The second is how can we efficiently extract or search (or classification) the original data from the encrypted and obfuscated information; The third but not the last is how to prevent the attacker to analyze the data so as to preserve the user privacy (i.e., big data can describe the activities of us).

Information Leakage. Information leakage is a major concern in open networks such as Internet of Things, cloud computing, outsourced big data etc. In the sensitive leakage case, a malicusou user is able to gain some sensitive information about the keys, the randomness and even the intermediate results from the computation performed on the devices and the monitor of secret channels by injecting the virus or worms.

Secure Outsourcing and Multi-party Computation. In Secure Multi-party Ccomputations (SMC), mutually distrustful parties need to securely and and jointly perform a computationa but cannot afford to reveal their inputs to each other, which have appealing applications such as e-auction, e-voting, gene sequences and fingerprints matching, privacy-preserving function evaluation etc. Defining model and improving effiency are also on-going research in this field.

SMC protocols support the parties that have similar computation ability. However, if the protocol is executed in unbalanced computation device or nodes, outsourcing is a judicious choice to optimize the performance. For example, outsourcing storage allows us to store big data in cloud system, and outsroucing computation helps less computation node (i.e., mobile phone or WSN node) in evaluating the computation in high-speed equipments (i.e., PC or mainframe), and then increase the processing speed. However, outsourcing might associate with the other perhaps untrusted client or server, and dishonest workers may modify and return plausible results without performing the actual work. The security consideration should be not only concerned with getting the result of the outsourced function, protecting the sensitive input and function, but also with the user being able to verify the result with significantly less computational cost than actually computing the function.